Title :
Semi-Blind Channel Estimation Based on Signal Subspace Tracking for MIMO-OFDM System
Author :
Cai Liping ; Ma Junfei
Author_Institution :
Coll. of Comput. & Commun. Eng., China Univ. of Pet., Dongying, China
Abstract :
In order to solve the problems of high computational complexity, large amount of computing which semi-blind channel estimation algorithm based on subspace has for MIMO-OFDM system, the MIMO-OFDM semi-blind channel estimation algorithm based on the projection approximation subspace tracking (PAST) is proposed. The decomposition of signal subspace is equivalent to solving unconstrained optimization problem. The unconstrained optimization problem is simplified into exponent-weighted least squares problem by introducing PAST method. To ensure tracking signal subspace accurately and signal orthogonal in each iteration process, the orthogonal weighted matrix is introduced. Theoretical analysis and simulation results show that the improved algorithm accelerates the convergence rate and reduces the complexity of computing while maintains the performance unchanged compared to the original algorithm.
Keywords :
MIMO communication; OFDM modulation; channel estimation; computational complexity; iterative methods; least squares approximations; optimisation; MIMO-OFDM system; computational complexity; convergence rate; exponent-weighted least squares problem; iteration process; orthogonal weighted matrix; projection approximation subspace tracking; semiblind channel estimation; signal subspace decomposition; signal subspace tracking; unconstrained optimization problem; Algorithm design and analysis; Approximation algorithms; Channel estimation; Computational complexity; Least squares approximation; Least squares methods; Matrix decomposition; Optimization methods; Performance analysis; Signal processing;
Conference_Titel :
Information Science and Engineering (ICISE), 2009 1st International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4244-4909-5
DOI :
10.1109/ICISE.2009.1055